Fault detection by labeled Petri nets and time constraints

This paper generalizes a previous result on the diagnosis of discrete event systems in a Petri Net framework and based on Integer Linear Programming problem solutions. In particular, we assume that silent transitions model faults and both observable and unobservable transitions model the nominal system behavior. However, in this contribution observable transitions exhibit non determinism since several different transitions may share the same event label. Moreover, a timing structure of the events is considered. For this more general problem, a new fault detection strategy is devised, which enables to define a new diagnoser that detects faults in the new system setting. An example points out the efficiency of the proposed approach.